Kinetic modeling of multiplexed SERS nanoparticles for quantitative molecular phenotyping (QMP) of breast cancer Approximately 200,000 women are diagnosed with early-stage invasive breast cancer or carcinoma in situ each year, for which breast-conserving surgery (BCS), or lumpectomy, is the standard surgical treatment. A major challenge for BCS is to ensure that tumors are completely resected, as this is highly correlated with the rate of local recurrence. Unfortunately, many surgeries result in incomplete tumor removal, and re-excision rates range from 20 to 60%. Re-excision surgeries are costly, inconvenient for patients, increases the risk of iatrogenic injury, and can result in delayed adjuvant therapies with inferior patient outcomes. In this study, we aim to develop a wide-area quantitative molecular phenotyping (QMP) strategy to comprehensively image the final surgical margin surface of biopsy shavings routinely obtained during breast conserving surgeries. QMP utilizes surface-enhanced Raman scattering (SERS) nanoparticles (NPs) that are available in multiple ?flavors,? each of which emits a characteristic Raman fingerprint spectrum that allows for the quantification of large multiplexed mixtures of NPs with low-power laser illumination at a single wavelength. In preliminary studies, the QMP technology developed by PI Dr. Liu has been shown to enable the visualization of up to 4 tumor biomarkers at the surfaces of fresh breast tissues following a rapid topical staining (5-min) and rinse removal (20-s) protocol. While these previous studies utilized a ratiometric paired-agent imaging method to mitigate nonspecific effects and to quantify the relative expression of biomarker targets, the specific focus of this R21 proposal is to develop and validate a new kinetic-imaging method to enable absolute quantification of cell-surface receptor expression levels. The accurate quantification of receptor densities will provide a clinical advantage for the identification of receptor-positive tumors in women with diverse stromal characteristics, and for patients whose normal breast tissues express low levels of certain tumor biomarkers, albeit at a differential level compared to tumors. This exploratory study will develop an automated device that enables multi-stage staining, rinsing, and imaging of tissue specimens (Aim 1) in order to visualize temporal binding kinetics, and to model these kinetics (Aim 2) such that receptor expression levels can be accurately quantified. Validation studies will utilize freshly excised tissues from mice implanted with well-characterized biomarker-positive cell lines, as well as fresh human tissue specimens, and will demonstrate that our QMP method enables more-accurate quantitative imaging of biomarker expression compared with a single-time-point ratiometric imaging method. The technologies developed in this exploratory study will pave the way for future clinical studies to examine the accuracy (sensitivity and specificity) of tumor detection for intraoperative lumpectomy guidance. !